Fault Diagnosis for Maglev System Based on Improved Principal Component Analysis

被引：0

作者：

Xue, Song ^{[1
]}

Li, Xiaolong ^{[1
]}

Long, Zhiqiang ^{[1
]}

机构：

[1] Natl Univ Def Technol, Coll Mechaeron Engn & Automat, Changsha 410073, Hunan, Peoples R China

来源：

2008 7TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-23 | 2008年

关键词：

PCA; maglev train; fault diagnosis; tracking-differentiator;

D O I：

10.1109/WCICA.2008.4594275

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The problem of sensor-fault detection and diagnosis (FDD) of maglev system was studied based on principal component analysis (PCA). First, the mathematic model of single electromagnet suspension system was constructed, and then a sensor-FDD strategy was designed for it based on PCA. The performance of the FDD strategy was simulated. At last, tracking-differentiator (TD) was introduced into the sensor-FDD system. The result of simulation shows that the FDD strategy based on PCA combined with TD are superior to that based on PCA only in the precision of FDD and to that based on PCA combined with exponentially weighted moving average (EWMA) in time consuming.

引用

页码：8563 / 8568

页数：6